The outstanding support during all project phases and the straightforward way of requesting or extending a de.NBI Cloud application make the de.NBI Cloud an ideal platform for data-driven bioinformatic research. Read more…

Peter Ebert, Heinrich Heine University Düsseldorf, Institute for Medical Biometry and Bioinformatics

Through all of these projects, we have greatly appreciated the interaction with the de.NBI cloud team who has provided tremendous support and responded quickly to various demands for extensions and provided constant expertise to set up the infrastructure.
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Carl Herrmann – Medical Faculty Heidelberg, Health Data Science Unit – Biomedical Genomics Group

A major advantage of the de.NBI cloud is that we save time managing hardware and servers and instead focus on the actual science. Compared to other cloud infrastructure the de.NBI cloud provides direct and uncomplicated contact with the support team and admins.
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Dr. Matthias König – Humboldt-University Berlin, Systems Medicine of the Liver

Having the de.NBI Cloud, we can easily crunch through some large-scale metabolomics data sets using the containerised workloads we have developed in the PhenoMeNal-H2020.EU project. Scaling up in case of peak usage, e.g. in a training event, works like a charm.
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Steffen Neumann – Leibniz Institute of Plant Biochemistry

We use the de.NBI Cloud since 2017 to serve the MetaProteomeAnalyzer software to the metaproteomics community. Now, three times more users analyses their experiments using our software. Our next step is to evolve the software to an analytical platform for mass spectrometry experiments on the de.NBI Cloud using automatic scalable cloud architecture, the SMACK stack. Read more…

Roman Zoun – Otto von Guericke University of Magdeburg

Thanks to de.NBI Cloud, we are able to conduct almost all aspects of large-scale microbial community analyses, such as 16S amplicon analysis, metagenomics, metatranscriptomics and metaproteomics. With the availability and support of de.NBI Cloud, we have created a working and learning environment for undergraduate, PhD students and Postdocs to develop and improve their reproducible workflows and analyses. Read more…

Johannes Werner – Leibniz-Institute for Baltic Sea Research